crazy_marksman

How do you deal with security and access control across postgres and pinecone?

Another option is to cold email investors in case you are open to working at a start up.

So much hate :( I agree the repo needs some clean up to be useful. Nevertheless, good collection!

Key Insights:

1. Many database back up their data in a sqlite database. Some even push vectors into sqlite, but others store vectors in their own format.

2. Qdrant has higher client connection and index initialization time that can shadow its benefit on fast and accurate vector search.

Are you using RAG to synthesize responses?

Made it easier to document code. You can send the function as context, and it will generate a well-formatted docstring that accomplishes 90% of the task!

I don't believe there is a solution otherwise. All you can do is cross join.

I appreciate your view on using LLMs in production. However, I think the ability to use ML/AI directly within databases is a significant step forward. Most production systems already rely on predictions, so the idea of using them without leaving the database is both interesting and valuable.

Awesome work! What is the preferred way of adding embeddings in sqlite table?

Is there a token limit for the train step? Like length of documentation, number of example SQL queries?

Impressive! Quick question - is it possible to generate sql for a slight variant of sql? My project augments standard sql with a few new constructs.

Some academic startups do come up with novel ideas, but the novelty typically lies in the technology rather than the marketing standpoint. For example, Anyscale offers a novel technology, but from a business perspective, it is a generic scalable training framework.